Sections

Introduction

I've always been fascinated with patterns. It doesn't really matter what
kind of patterns; I've played with networks, leaves and leaf venation,
branches, lightning, flocking, tracing outlines
of shapes, river formation, rock sediments, landscapes, slime mold, lichens,
reaction-diffusion,
cellular
automaton, some fractals, and a few other things. I think what I
enjoy the most is how complex and intricate results you can get from a set
of simple rules.

Recently I've been particularly interested in biological patterns, and
differential growth. My background is in numerical mathematics, not
biology. So I have limited knowledge of how biological systems actually
work. Even so, I've been experimenting quite a lot with recreating various
biological behaviours. Part of the challenge is to try to recreate some
pattern or behaviour with as few and as simple rules as possible.

Sometimes I manage to recreate the phenomenon I set out to create, and
sometimes not. More often than not I get something interesting, even if it
is not always what I expected.

A Confession

In the interest of disclosure I should point out that I sometimes base my
work on the ideas that I have seen done elsewhere by a number of other
generative artists. Most notably Jared Tarbell and Nervous System. For instance the
algorithm I named Orbitals (image
below) is very heavily based on Happy
Place by Tarbell.

I point this out because I have always found it hard to know where a
piece of software—and in my particular case, the images generated by that
software—is novel enough to be viewed as a separate work.

Inconvergent

I started working with generative algorithms when I was supposed to be
studying for my exams at university. For that reason I bought the domain
name inconvergent.net, as a joke on me diverging from my
studies. The first thing I did was to copy several of Tarbell's algorithms
using Javascript/Canvas. After a while I started getting a few other ideas
of my own.

Apart from Orbitals, the first algorithm I got working was Hyphae. It came to me when I was trying to recreate the
behaviour of Hyphae
by Nervous System. At this point I hadn't realized how complicated that
algorithm actually is, and I spent way too much time trying and failing to
get it anywhere near decent. I implemented it later, and you can read the
Siggraph
paper describing it if you are interested. It is a fascinating
read!

Code

I make almost all of my code available at Github. All the following
sections have a link to the corresponding repository. Unfortunately not all
of it is entirely well documented or up to date.